Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Specification and Analysis of Open-Ended Systems with CARMA

  • Conference paper
  • First Online:
Agent Environments for Multi-Agent Systems IV

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9068))

Abstract

Carma is a new language recently defined to support quantified specification and analysis of collective adaptive systems. It is a stochastic process algebra equipped with linguistic constructs specifically developed for modelling and programming systems that can operate in open-ended and unpredictable environments. This class of systems is typically composed of a huge number of interacting agents that dynamically adjust and combine their behaviour to achieve specific goals. A Carma model, termed a “collective”, consists of a set of components, each of which exhibits a set of attributes. To model dynamic aggregations, which are sometimes referred to as “ensembles”, Carma provides communication primitives based on predicates over the exhibited attributes. These predicates are used to select the participants in a communication. Two communication mechanisms are provided in the Carma language: multicast-based and unicast-based. A key feature of Carma is the explicit representation of the environment in which processes interact, allowing rapid testing of a system under different open world scenarios. The environment in Carma models can evolve at runtime, due to the feedback from the system, and it further modulates the interaction between components, by shaping rates and interaction probabilities.

This work is partially supported by the EU project QUANTICOL, 600708.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    For any denumerable set X, we let Dist(X) denote the set of probability distributions over X while \(\delta _{X}\) is a generic element in Dist(X).

  2. 2.

    Due to the symmetry of the considered model, any other location in the border presents similar results.

References

  1. Compagnoni, A., Giannini, P., Kim, C., Milideo, M., Sharma, V.: A calculus of located entities. In: Proceedings of DCM 2013 (2014)

    Google Scholar 

  2. Compagnoni, A., Sharma, V., Bao, Y., Libera, M., Suhkishvili, S., Bidinger, P., Bioglio, L., Bonelli, E.: Biospace: a modeling and simulation language for bacteria-materials interactions. ENTCS 293, 35–49 (2013)

    Google Scholar 

  3. Alrahman, Y., De Nicola, R., Loreti, M., Tiezzi, F., Vigo, R.: A calculus for attribute-based communication. In: Proceedings of SAC 2015 (2015, to appear)

    Google Scholar 

  4. Steiniger, A., Krüger, F., Uhrmacher, A.M.: Modeling agents and their environment in multi-level-DEVS. In: Proceedings of the 2012 Winter Simulation Conference, Berlin, Germany. IEEE (2012)

    Google Scholar 

  5. Bernardo, M., Gorrieri, R.: A tutorial on EMPA: a theory of concurrent processes with nondeterminism, priorities, probabilities and time. Theor. Comput. Sci. 202(1–2), 1–54 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  6. Bohnenkamp, H.C., D’Argenio, P.R., Hermanns, H., Katoen, J.: MODEST: a compositional modeling formalism for hard and softly timed systems. IEEE Trans. Softw. Eng. 32(10), 812–830 (2006)

    Article  Google Scholar 

  7. Bordini, R.H., Okuyama, F.Y., de Oliveira, D., Drehmer, G., Krafta, R.C.: The MAS-SOC approach to multi-agent based simulation. In: Lindemann, G., Moldt, D., Paolucci, M. (eds.) RASTA 2002. LNCS (LNAI), vol. 2934, pp. 70–91. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  8. Bortolussi, L., Hillston, J., Tribastone, M.: Fluid performability analysis of nested automata models. Electr. Notes Theor. Comput. Sci. 310, 27–47 (2015)

    Article  Google Scholar 

  9. Bortolussi, L., Policriti, A.: Hybrid dynamics of stochastic programs. Theor. Comput. Sci. 411(20), 2052–2077 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  10. Cardelli, L., Gordon, A.D.: Mobile ambients. Theor. Comput. Sci. 240(1), 177–213 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  11. Celaya, J.R., Desrochers, A.A., Graves, R.J.: Modeling and analysis of multi-agent systems using petri nets. JCP 4(10), 981–996 (2009)

    Google Scholar 

  12. Ciocchetta, F., Hillston, J.: Bio-PEPA: a framework for the modelling and analysis of biological systems. Theor. Comput. Sci. 410(33), 3065–3084 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  13. Maus, C., Rybacki, S., Uhrmacher, A.M.: Rule-based multi-level modelling of cell biological systems. BMC Syst. Biol. 5, 166 (2011)

    Article  Google Scholar 

  14. De Nicola, R., Latella, D., Massink, M.: Formal modeling and quantitative analysis of klaim-based mobile systems. In: Proceedings of the 2005 ACM Symposium on Applied Computing (SAC), Santa Fe, New Mexico, USA, 13–17 March 2005, pp. 428–435. ACM (2005)

    Google Scholar 

  15. De Nicola, R., Loreti, M., Pugliese, R., Tiezzi, F.: A formal approach to autonomic systems programming: the SCEL language. TAAS 9(2), 7 (2014)

    Article  Google Scholar 

  16. Feng, C., Hillston, J.: PALOMA: a process algebra for located Markovian agents. In: Norman, G., Sanders, W. (eds.) QEST 2014. LNCS, vol. 8657, pp. 265–280. Springer, Heidelberg (2014)

    Google Scholar 

  17. Feng, C., Hillston, J.: Speed-up of stochastic simulation of PCTMC models by statistical model reduction (2015, Submitted)

    Google Scholar 

  18. Galpin, V.: Modelling network performance with a spatial stochastic process algebra. In: Proceedings of International Conference on Advanced Information Networking and Applications, pp. 41–49. IEEE (2009)

    Google Scholar 

  19. Gilmore, S., Hillston, J., Kloul, L., Ribaudo, M.: PEPA nets: a structured performance modelling formalism. Perform. Eval. 54, 79–104 (2003)

    Article  MATH  Google Scholar 

  20. Helleboogh, A., Vizzari, G., Uhrmacher, A.M., Michel, F.: Modeling dynamic environments in multi-agent simulation. Auton. Agents Multi-Agent Syst. 14(1), 87–116 (2007)

    Article  Google Scholar 

  21. Hermanns, H., Herzog, U., Katoen, J.: Process algebra for performance evaluation. Theor. Comput. Sci. 274(1–2), 43–87 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  22. Hermanns, H., Rettelbach, M.: Syntax, semantics, equivalences and axioms for MTIPP. In: Herzog, U., Rettelbach, M. (eds.) Proceedings of 2nd Process Algebra and Performance Modelling Workshop (1994)

    Google Scholar 

  23. Hillston, J.: A Compositional Approach to Performance Modelling. CUP (1995)

    Google Scholar 

  24. Latella, D., Loreti, M., Massink, M., Senni, V.: Stochastically timed predicate-based communication primitives for autonomic computing. In: Bertrand, N., Bortolussi, L. (eds.) Proceedings Twelfth International Workshop on Quantitative Aspects of Programming Languages and Systems, QAPL 2014, Grenoble, France, 12–13 April 2014. EPTCS, vol. 154, pp. 1–16 (2014)

    Google Scholar 

  25. Bortolussi, L., Nicola, R.D., Galpin, V., Gilmore, S., Hillston, J., Latella, D., Loreti, M., Massink, M.: Carma: collective adaptive resource-sharing markovian agents. In: Proceedings of the Workshop on Quantitative Analysis of Programming Languages 2015 (2015, to appear)

    Google Scholar 

  26. Mili, R.Z., Steiner, R.: Modeling agent-environment interactions in adaptive MAS. In: Weyns, D., Brueckner, S.A., Demazeau, Y. (eds.) EEMMAS 2007. LNCS (LNAI), vol. 5049, pp. 135–147. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  27. Milner, R., Parrow, J., Walker, D.: A calculus of mobile processes. I. Inf. Comput. 100(1), 1–40 (1992)

    Article  MathSciNet  MATH  Google Scholar 

  28. John, M., Lhoussaine, C., Niehren, J., Uhrmacher, A.M.: The attributed pi calculus. In: Heiner, M., Uhrmacher, A.M. (eds.) CMSB 2008. LNCS (LNBI), vol. 5307, pp. 83–102. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  29. Priami, C.: Stochastic \(\pi \)-calculus. Comput. J. 38(7), 578–589 (1995)

    Article  Google Scholar 

  30. Regev, A., Panina, E.M., Silverman, W., Cardelli, L., Shapiro, E.Y.: Bioambients: an abstraction for biological compartments. Theor. Comput. Sci. 325(1), 141–167 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  31. Saunier, J., Balbo, F., Pinson, S.: A formal model of communication and context awareness in multiagent systems. J. Logic Lang. Inf. 23(2), 219–247 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  32. Tribastone, M., Gilmore, S., Hillston, J.: Scalable differential analysis of process algebra models. IEEE Trans. Softw. Eng. 38(1), 205–219 (2012)

    Article  Google Scholar 

  33. Weyns, D., Holvoet, T.: A formal model for situated multi-agent systems. Fundam. Inform. 63(2–3), 125–158 (2004)

    MathSciNet  MATH  Google Scholar 

  34. Weyns, D., Omicini, A., Odell, J.: Environment as a first class abstraction in multiagent systems. Auton. Agents Multi-Agent Syst. 14(1), 5–30 (2007)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Michele Loreti .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Hillston, J., Loreti, M. (2015). Specification and Analysis of Open-Ended Systems with CARMA. In: Weyns, D., Michel, F. (eds) Agent Environments for Multi-Agent Systems IV. Lecture Notes in Computer Science(), vol 9068. Springer, Cham. https://doi.org/10.1007/978-3-319-23850-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23850-0_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23849-4

  • Online ISBN: 978-3-319-23850-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics